access icon free Quadrotor circumnavigation of an unknown moving target using camera vision-based measurements

This study proposes a vision-based motion estimation and target tracking algorithm for a quadrotor unmanned aerial vehicle circumnavigation around a moving mobile target whose velocity is unknown and time varying. In this study, the authors assume that the quadrotor is equipped with onboard downward-looking camera, as a means to determine position of the quadrotor relative to the target. The proposed circumnavigation control algorithm relies essentially on two distinct phases, namely the virtual target tracking and the circumnavigation phase. To prepare for these phases, a predefined sphere, with a desired radius having the moving target position as its centre, is constructed along with a virtual target point that can move on its surface. During the whole tracking procedure, the quadrotor is first commanded to reach the virtual target point located at the projection of the ground vehicle's position onto the surface area of the sphere. When the quadrotor's position and velocity approaches the virtual target point with a given accuracy, the second phase is initiated to provide the quadrotor with more precise guidance to start orbiting at a specific height from level ground around the moving target. In this manner, the virtual target point is given the ability to manoeuvre itself in a circular motion above the moving target. The developed orbit manoeuvre uses an estimate of the moving target's velocity, obtained from a predictor scheme able to achieve velocity estimation as fast as possible.

Inspec keywords: target tracking; aircraft control; mobile robots; autonomous aerial vehicles; path planning; robot vision; helicopters; motion estimation

Other keywords: position determination; quadrotor unmanned aerial vehicle circumnavigation control algorithm; predictor scheme; camera vision-based measurements; circumnavigation phase; virtual target tracking; virtual target point; onboard downward-looking camera; unknown moving target; moving target velocity estimation; vision-based motion estimation algorithm

Subjects: Computer vision and image processing techniques; Mobile robots; Optical, image and video signal processing; Spatial variables control; Telerobotics; Aerospace control; Image sensors

References

    1. 1)
      • 2. Deghat, M., Shames, I., Anderson, B.D.O., et al: ‘Target localization and circumnavigation using bearing measurements in 2d’. Proc. of the 49th Conf. on Decision and Control, Atlanta, GA, USA, 15–17 December 2010.
    2. 2)
      • 20. Hehn, M., D'Andrea, R.: ‘Real-time trajectory generation for interception maneuvers with quadrocopters’. IEEE Int. Conf. Intelligent Robots and Systems (IROS), Hong Kong, 7–12 October 2012.
    3. 3)
      • 18. Thomas, J., Loianno, G., Daniilidis, K.,, et al: ‘Visual servoing of quadrotors for perching b hanging from cylindrical objects’, IEEE Robot. Autom. Lett., 2016, 1, (1), pp. 5764.
    4. 4)
      • 16. Tournier, G.P., Valentiy, M., How, J.P.: ‘Estimation and control of a quadrotor vehicle using monocular vision and moiré patterns’. AIAA Guidance, Navigation, and Control Conf. and Exhibit, Keystone, Colorado, 21–24 August 2006.
    5. 5)
      • 10. Ma, L., Cao, C., Hovakimyan, N., et al: ‘Adaptive vision-based guidance law with guaranteed performance bounds’, J. Guid. Control Dyn., 2010, 33, (3), pp. 834852.
    6. 6)
      • 7. Cao, Y., Muse, J., Casbeer, D., et al: ‘Circumnavigation of an unknown target using uavs with range and range rate measurements’. Proc. of the 52nd Conf. on Decision and Control, Firenze, 10–13 December 2013.
    7. 7)
      • 6. Matveev, A.S., Teimoori, H., Savkin, A.V.: ‘Range-only measurements based target following for wheeled mobile robots’, Automatica, 2011, 47, (1), pp. 177184.
    8. 8)
      • 24. Ghommam, J., Charland, G., Saad, M.: ‘Three-dimensional constrained tracking control via exact differentiation estimator of a quadrotor helicopter’, Asian J. Control, 2015, 17, (3), pp. 10931103.
    9. 9)
      • 21. Do, K.D.: ‘Global tracking control of underactuated odins in three-dimensional space’, Int. J. Control, 2013, 86, (2), pp. 183196.
    10. 10)
      • 4. Fidan, B., Dasgupta, S., Anderson, B.D.O.: ‘Adaptive range-measurement-based target pursuit’, Int. J. Adapt. Control Signal Process., 2013, 27, (1–2), pp. 6681.
    11. 11)
      • 23. Lee, T., Leok, M., Harris McClamroch, N.: ‘Nonlinear robust tracking control of a quadrotor uav on se(3)’. Proc. of the 2012 American Control Conf., Fairmont Queen Elizabeth, Montreal, Canada, December 2012.
    12. 12)
      • 15. Shen, S., Mulgaonkar, Y., Michael, N., et al: ‘Vision-based state estimation for autonomous rotorcraft mavs in complex environments’. IEEE Int. Conf. Robotics and Automation (ICRA), Las Vegas, Nevada, 6–10 May 2013.
    13. 13)
      • 5. Shames, I.I., Dasgupta, S., Fidan, B., et al: ‘Circumnavigation using distance measurements under slow drift’, IEEE Trans. Autom. Control, 2012, 57, (4), pp. 889903.
    14. 14)
      • 14. Shen, S., Mulgaonkar, Y., Michael, N., et al: ‘Vision-based state estimation and trajectory control towards high-speed flight with a quadrotor’. Robotics: Science and Systems', Las Vegas, Nevada, 2013.
    15. 15)
      • 8. Dobrokhodov, V., Kaminer, I., Jones, K., et al: ‘Vision-based tracking and motion estimation for moving targets using unmanned air vehicles’, J. Guid. Control Dyn., 2008, 31, (4), pp. 907917.
    16. 16)
      • 12. Rao, R., Kumar, V., Taylor, C.: ‘Visual servoing of a ugv from a uav using differential flatness’. IEEE Int. Conf. Intelligent Robots and Systems, Las Vegas, Nevada, 27–31 October 2003.
    17. 17)
      • 22. Khalil, H.K.: ‘Nonlinear systems’ (Prentice-Hall, Englewood Cliffs, NJ, 2002, 3rd edn.).
    18. 18)
      • 25. Liu, H., Danjun, L., Zhong, Y.: ‘Robust trajectory tracking control of uncertain quadrotors without linear velocity measurements’, IET Control Theory Appl., 2015, 9, (11), pp. 17461754.
    19. 19)
      • 11. Pascoal, A., Kaminer, I., Oliveira, P.: ‘Navigation system design using time-varying complementary filters’, IEEE Trans. Aerosp. Electron. Syst., 2000, 36, (4), pp. 10991114.
    20. 20)
      • 19. Thomas, J., Loianno, G., Sreenath, K., et al: ‘Toward image based visual servoing for aerial grasping and perching’. IEEE Int. Conf. Robotics and Automation (ICRA), Hong Kong, May 31–7 June 2014.
    21. 21)
      • 1. Deghat, M., Davis, E., See, T., et al: ‘Target localization and circumnavigation by a non-holonomic robot’. IEEE Int. Conf. Intelligent Robots and Systems, Vilamoura, Algarve, Portugal, 7–12 October 2012.
    22. 22)
      • 3. Fidan, B., Dandach, S., Dasgupta, S., et al: ‘A continuous time linear adaptive source localization algorithm robust to persistent drift’, Syst. Control Lett., 2009, 58, (1), pp. 716.
    23. 23)
      • 17. Mebarki, R., Lippiello, V., Siciliano, B.: ‘Nonlinear visual control of unmanned aerial vehicles in gps-denied environments’, IEEE Trans. Robot., 2015, 31, (4), pp. 10041017.
    24. 24)
      • 13. Wang, I., Dobrokhodov, V., Kaminer, I., et al: ‘On vision-based target tracking and range estimation for small uavs’. AIAA Guidance, Navigation and Control Conf. (AIAA Paper)', San Francisco, August 2005, pp. 20056401.
    25. 25)
      • 27. Christofides, P.D., , Teel, A.R.: ‘Singular perturbations and input-to-state stability’, IEEE Trans. Autom. Control, 1996, 41, (11), pp. 16451650.
    26. 26)
      • 26. Liu, H., Wang, X., Zhong, Y.: ‘Robust position control of a lab helicopter under wind disturbances’, IET Control Theory Appl., 2014, 15, (8), pp. 15551565.
    27. 27)
      • 9. Hespanha, J., Yakimenko, O., Kaminer, I., et al: ‘Linear parametrically varying systems with brief instabilities: an application to integrated vision/imu navigation’, IEEE Trans. Aerosp. Electron. Syst., 2004, 40, (3), pp. 889902.
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